/network/neo4j
Foundation of the ƒxyz knowledge graph. Relationship-first queries across financial entities, currencies, and members.
Purpose-built for storing and traversing highly connected data with optimal performance
Intuitive query language designed specifically for pattern matching in graphs
Navigate complex relationship networks in milliseconds, regardless of data size
Model complex financial relationships, ownership structures, and regulatory connections
Identify suspicious patterns and connections that traditional databases would miss
Link disparate data sources to build complete entity profiles
Trace the ripple effects of changes across interconnected financial systems
Cypher queries across financial entities, regulatory frameworks, and market relationships.